Publications

Background/Objectives: Concurrent opioid (OPI) and benzodiazepine (BZD) use may exacerbate injurious fall risk (e.g., falls and fractures) compared to no use or use alone. Yet, patients may need concurrent OPI-BZD use for co-occurring conditions (e.g., pain and anxiety). Therefore, we examined the association between longitudinal OPI-BZD dosing patterns and subsequent injurious fall risk. Methods: We conducted a retrospective cohort study including non-cancer fee-for-service Medicare beneficiaries initiating OPI and/or BZD in 2016-2018. We identified OPI-BZD use patterns during the 3 months following OPI and/or BZD initiation (i.e., trajectory period) using group-based multi-trajectory models. We estimated the time to first injurious falls within the 3-month post-trajectory period using inverse-probability-of-treatment-weighted Cox proportional hazards models. Results: Among 622,588 beneficiaries (age ≥ 65 = 84.6%, female = 58.1%, White = 82.7%; having injurious falls = 0.45%), we identified 13 distinct OPI-BZD trajectories: Group (A): Very-low OPI-only (early discontinuation) (44.9% of the cohort); (B): Low OPI-only (rapid decline) (15.1%); (C): Very-low OPI-only (late discontinuation) (7.7%); (D): Low OPI-only (gradual decline) (4.0%); (E): Moderate OPI-only (rapid decline) (2.3%); (F): Very-low BZD-only (late discontinuation) (11.5%); (G): Low BZD-only (rapid decline) (4.5%); (H): Low BZD-only (stable) (3.1%); (I): Moderate BZD-only (gradual decline) (2.1%); (J): Very-low OPI (rapid decline)/Very-low BZD (late discontinuation) (2.9%); (K): Very-low OPI (rapid decline)/Very-low BZD (increasing) (0.9%); (L): Very-low OPI (stable)/Low BZD (stable) (0.6%); and (M): Low OPI (gradual decline)/Low BZD (gradual decline) (0.6%). Compared with Group (A), six trajectories had an increased 3-month injurious falls risk: (C): HR = 1.78, 95% CI = 1.58-2.01; (D): HR = 2.24, 95% CI = 1.93-2.59; (E): HR = 2.60, 95% CI = 2.18-3.09; (H): HR = 2.02, 95% CI = 1.70-2.40; (L): HR = 2.73, 95% CI = 1.98-3.76; and (M): HR = 1.96, 95% CI = 1.32-2.91. Conclusions: Our findings suggest that 3-month injurious fall risk varied across OPI-BZD trajectories, highlighting the importance of considering both dose and duration when assessing injurious fall risk of OPI-BZD use among older adults.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been associated with an increased risk of stroke. It remains unclear whether the risk of stroke associated with a diagnosis of COVID-19 differed with oral anticoagulation (OAC) use. The aim of this study was to evaluate the association between COVID-19 infection, OAC use, and stroke in patients with atrial fibrillation (AF).

METHODS: A retrospective cohort study was conducted in individuals with established AF using data from Optum's deidentified Clinformatics® Data Mart Database. Cox proportional hazard models with time-dependent variables were employed to assess the association between possession of OAC, COVID-19 diagnosis in both inpatient and outpatient setting, and time to ischemic stroke.

RESULTS: A total of 561,758 individuals aged 77 ± 10 were included in the study, with a mean follow up time of 1.3 years. OAC use was associated with a reduced stroke risk [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.82-0.88]. COVID-19 infection was associated with an increased risk of stroke (HR 2.11, 95% CI 1.87-2.38); this increased risk was particularly pronounced for patients diagnosed with an inpatient diagnosis of COVID-19 (HR 3.95, 95% CI 3.33-4.68). There was no significant interaction between OAC use and COVID-19 diagnosis (p value = 0.96). As a result, the relative increase in stroke risk associated with COVID-19 did not differ between patients on OAC (HR 2.12; 95% CI 1.71-2.62) and those not on OAC (HR 2.11; 95% CI 1.83-2.43).

CONCLUSION: In a nationwide sample of patients with established AF, we found the relative increase in stroke risk associated with COVID-19 was independent of OAC use.

BACKGROUND: Veterans dually enrolled in the Veterans Health Administration (VA) and Medicare commonly experience downstream services as part of a care cascade after an initial low-value service. Our objective was to characterize the frequency and cost of low-value cervical cancer screening and subsequent care cascades among Veterans dually enrolled in VA and Medicare.

METHODS: This retrospective cohort study used VA and Medicare administrative data from fiscal years 2015 to 2019. The study cohort was comprised of female Veterans aged >65 years and at low risk of cervical cancer who were dually enrolled in VA and Medicare. Within this cohort, we compared differences in the rates and costs of cascade services related to low-value cervical cancer screening for Veterans who received and did not receive screening in FY2018, adjusting for baseline patient- and facility-level covariates using inverse probability of treatment weighting.

RESULTS: Among 20,972 cohort-eligible Veterans, 494 (2.4%) underwent low-value cervical cancer screening with 301 (60.9%) initial screens occurring in VA and 193 (39%) occurring in Medicare. Veterans who were screened experienced an additional 26.7 (95% CI, 16.4-37.0) cascade services per 100 Veterans compared to those who were not screened, contributing to $2919.4 (95% CI, -265 to 6104.7) per 100 Veterans in excess costs. Care cascades consisted predominantly of subsequent cervical cancer screening procedures and related outpatient visits with low rates of invasive procedures and occurred in both VA and Medicare.

CONCLUSIONS: Veterans dually enrolled in VA and Medicare commonly receive related downstream tests and visits as part of care cascades following low-value cervical cancer screening. Our findings demonstrate that to fully capture the extent to which individuals are subject to low-value care, it is important to examine downstream care stemming from initial low-value services across all systems from which individuals receive care.

STUDY OBJECTIVE: The COVID-19 pandemic disrupted multiple aspects of the health care system, including the diagnosis and control of chronic conditions. This study aimed to quantify pandemic-related changes in the rates of clinical events among patients with atrial fibrillation (AF).

DESIGN/SETTING/PARTICIPANTS: In this retrospective cohort study, we identified individuals with established AF at any time before 2019 using de-identified Optum's Clinformatics® Data Mart, and followed them from 3/18/2019 to death, or disenrollment, or the end of the study (09/30/2021).

MAIN OUTCOME: Rates of clinical event, including all-cause hospitalization, ischemic stroke, and bleeding. We constructed interrupted time series to test changes in outcomes after the onset of the COVID-19 pandemic (3/11/2020, date of pandemic declaration). We then identified the first month after the start of the pandemic in which outcomes returned to pre-pandemic levels.

RESULTS: A total of 561,758 patients, with a mean age of 77 ± 9.9 years, were included in the study. The monthly incidence rate of all-cause hospitalization decreased from 2.8 % in the period immediately before the pandemic declaration to 1.7 % in the period immediately after, with p-value for level change<0.001. The rate of new ischemic stroke diagnoses decreased from 0.28 % in the period immediately before pandemic declaration to 0.20 % in the period immediately after, and the rate of major bleeding diagnoses from 0.81 % to 0.59 %, both p-values for level change<0.01. The incidence rate of ischemic stroke and bleeding events returned to pre-pandemic levels in October and November 2020, respectively.

CONCLUSIONS: The COVID-19 pandemic was associated with a decrease in health care visits for ischemic stroke and bleeding in a nationwide cohort of patients with established AF.

BACKGROUND: Integrating advanced machine-learning (ML) algorithms into clinical practice is challenging and requires interdisciplinary collaboration to develop transparent, interpretable, and ethically sound clinical decision support (CDS) tools. We aimed to design a ML-driven CDS tool to predict opioid overdose risk and gather feedback for its integration into the University of Florida Health (UFHealth) electronic health record (EHR) system.

METHODS: We used user-centered design methods to integrate the ML algorithm into the EHR system. The backend and UI design sub-teams collaborated closely, both informed by user feedback sessions. We conducted seven user feedback sessions with five UF Health primary care physicians (PCPs) to explore aspects of CDS tools, including workflow, risk display, and risk mitigation strategies. After customizing the tool based on PCPs' feedback, we held two rounds of one-on-one usability testing sessions with 8 additional PCPs to gather feedback on prototype alerts. These sessions informed iterative UI design and backend processes, including alert frequency and reappearance circumstances.

RESULTS: The backend process development identified needs and requirements from our team, information technology, UFHealth, and PCPs. Thirteen PCPs (male = 62%, White = 85%) participated across 7 user feedback sessions and 8 usability testing sessions. During the user feedback sessions, PCPs (n = 5) identified flaws such as the term "high risk" of overdose potentially leading to unintended consequences (e.g., immediate addiction services referrals), offered suggestions, and expressed trust in the tool. In the first usability testing session, PCPs (n = 4) emphasized the need for natural risk presentation (e.g., 1 in 200) and suggested displaying the alert multiple times yearly for at-risk patients. Another 4 PCPs in the second usability testing session valued the UFHealth-specific alert for managing new or unfamiliar patients, expressed concerns about PCPs' workload when prescribing to high-risk patients, and recommended incorporating the details page into training sessions to enhance usability.

CONCLUSIONS: The final backend process for our CDS alert aligns with PCP needs and UFHealth standards. Integrating feedback from PCPs in the early development phase of our ML-driven CDS tool helped identify barriers and facilitators in the CDS integration process. This collaborative approach yielded a refined prototype aimed at minimizing unintended consequences and enhancing usability.

IMPORTANCE: Drug shortages are a persistent public health issue that increased during the COVID-19 pandemic. Both the US and Canada follow similar regulatory standards and require reporting of drug-related supply chain issues that may result in shortages. However, it is unknown what proportion are associated with meaningful shortages (defined by a significant decrease in drug supply) and whether differences exist between Canada and the US.

OBJECTIVE: To compare how frequently reports of drug-related supply chain issues in the US vs Canada were associated with drug shortages.

DESIGN, SETTING, AND PARTICIPANTS: Longitudinal cross-sectional study conducted from January 2023 to March 2024 using drug-related reports of supply chain issues from 2017 to 2021 that were less than 180 days apart in Canada and the US. Shortages were assessed using data from the IQVIA Multinational Integrated Data Analysis database, comprising 89% of US and 100% of Canadian drug purchases.

EXPOSURE: Country (Canada vs US), timing of report issuance (before vs after the COVID-19 pandemic), and characteristics of the supply chain prior to the reports of drug-related supply chain issues (including World Health Organization essential medicine status, Health Canada tier 3 medicine [moderate risk classification], whether there was sole-source manufacturing of the drug, the formulation, the price per unit, ≥20 years since drug approval, and the number of therapeutic alternatives).

MAIN OUTCOMES AND MEASURES: A drug shortage (a decrease of ≥33% in monthly purchased standardized drug units) within 12 months, relative to the average units purchased during the 6 months prior to the report of supply chain issues to a US or Canadian reporting system.

RESULTS: Among the 104 drug-related reports of supply chain issues in both countries, 49.0% (95% CI, 39.3%-59.7%) were associated with drug shortages in the US vs 34.0% (95% CI, 25.0%-45.0%) in Canada (adjusted hazard ratio [HR], 0.53 [95% CI, 0.36-0.79]). The lower risk of drug shortages in Canada vs the US was consistent before the COVID-19 pandemic (adjusted HR, 0.47 [95% CI, 0.30-0.75]) and after the pandemic (adjusted HR, 0.31 [95% CI, 0.15-0.66]). After combining reports of supply chain issues in both countries, the shortage risk was double for sole-sourced drugs (adjusted HR, 2.58 [95% CI, 1.57-4.24]) and nearly half for Canadian tier 3 medicines (moderate risk) (adjusted HR, 0.56 [95% CI, 0.32-0.98]).

CONCLUSIONS AND RELEVANCE: Drug-related reports of supply chain issues were 40% less likely to result in meaningful drug shortages in Canada compared with the US. These findings highlight the need for international cooperation between countries to curb the effects of drug shortages and improve resiliency of the supply chain for drugs.

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Twenty-one U.S. states have passed recreational cannabis laws as of November 2022. Cannabis may be a substitute for prescription opioids in the treatment of chronic pain. Previous studies have assessed recreational cannabis laws' effects on opioid prescriptions financed by specific private or public payers or dispensed to a unique endpoint. Our study adds to the literature in three important ways: by (1) examining these laws' impacts on prescription opioid dispensing across all payers and endpoints, (2) adjusting for important opioid-related policies such as opioid prescribing limits, and (3) modeling opioids separately by type. We implement two-way fixed-effects regressions and leverage variation from eleven U.S. states that adopted a recreational cannabis law (RCL) between 2010 and 2019. We find that RCLs lead to a reduction in codeine dispensed at retail pharmacies. Among prescription opioids, codeine is particularly likely to be used non-medically. Thus, the finding that RCLs appear to reduce codeine dispensing is potentially promising from a public health perspective.